Frequently Asked Questions

1. What is CRCView?

CRC stands for the Chinese Restaurant Cluster, a Dirichlet process model-based clustering algorithm recently developed by Dr. Steve Qin. CRCView is a web-based system for microarray data analysis using the CRC algorithm. CRCView allows flexible input data format and rich graphical illustration on CRC clustering results. CRCView also incorporates BioConductor Heatmap and GOStats allowing useful result validating and interpretation.

2. What is the benefit of CRCView analysis over standard cluster approaches?

CRC has the following features comparing to other clustering tools: 1) able to infer number of clusters, 2) able to cluster genes displaying time-shifted and/or inverted correlations, 3) able to tolerate missing genotype data and 4) provide confidence measure for clusters generated. Here is some more details on why you should try CRC for your microarray data analysis. For details, you can follow the link and find a elaborated explanation in http://www.sph.umich.edu/csg/qin/CRC/.

3. Who are primary CRCView users?

Biologists seeking a powerful and user-friendly method for clustering analysis, visualization, and result interpretation specifically for microarray data.

4. Do I need to register and log in to use CRCView?

You don't need to log in to browse the general CRC information. However, you are required to log in to submit your data and to use the CRC analysis tools. Registration and login is free. This mechanism provides more privacy and also allows you to store your data and analysis results for later use.